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      Ellagic acid and its metabolites urolithins A/B ameliorate most common disease phenotypes in cellular and mouse models for lysosomal storage disorders by enhancing extracellular vesicle secretion

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          Abstract

          <p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="first" dir="auto" id="d1876877e158">Niemann Pick diseases types A (NPDA) and C (NPDC) are lysosomal storage disorders (LSDs) leading to cognitive impairment, neurodegeneration, and early death. NPDA and NPDC have different genetic origins, being caused by mutations in the acid sphingomyelinase (ASM) or the cholesterol transport protein NPC1, respectively. However, they share a common pathological hallmark in the accumulation of lipids in the endolysosomal compartment. Here, we tested the hypothesis that polyphenols reduce lipid overload in NPD cells by enhancing the secretion of extracellular vesicles (ECVs). We show that among the polyphenols tested, the ellagic acid metabolites, urolithin A and B, were the safest and most efficient in increasing ECV secretion. They reduced levels of accumulating lipids and lysosomal size and permeabilization in cultured bone marrow-derived macrophages and neurons from ASMko and NPC1 mutant mice, which mimic NPDA and NPDC, respectively. Moreover, oral treatment with ellagic acid reduced lipid levels, ameliorated lysosomal alterations, and diminished microglia activation in the brain of NPD mice. These results support the therapeutic value of ECV secretion and polyphenols for NPDs, which may also help treat other LSDs characterized by intracellular lipid overload. </p>

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          Most cited references53

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          A SIMPLE METHOD FOR THE ISOLATION AND PURIFICATION OF TOTAL LIPIDES FROM ANIMAL TISSUES

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            Communication by Extracellular Vesicles: Where We Are and Where We Need to Go.

            In multicellular organisms, distant cells can exchange information by sending out signals composed of single molecules or, as increasingly exemplified in the literature, via complex packets stuffed with a selection of proteins, lipids, and nucleic acids, called extracellular vesicles (EVs; also known as exosomes and microvesicles, among other names). This Review covers some of the most striking functions described for EV secretion but also presents the limitations on our knowledge of their physiological roles. While there are initial indications that EV-mediated pathways operate in vivo, the actual nature of the EVs involved in these effects still needs to be clarified. Here, we focus on the context of tumor cells and their microenvironment, but similar results and challenges apply to all patho/physiological systems in which EV-mediated communication is proposed to take place.
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              Ceramide triggers budding of exosome vesicles into multivesicular endosomes.

              Intraluminal vesicles of multivesicular endosomes are either sorted for cargo degradation into lysosomes or secreted as exosomes into the extracellular milieu. The mechanisms underlying the sorting of membrane into the different populations of intraluminal vesicles are unknown. Here, we find that cargo is segregated into distinct subdomains on the endosomal membrane and that the transfer of exosome-associated domains into the lumen of the endosome did not depend on the function of the ESCRT (endosomal sorting complex required for transport) machinery, but required the sphingolipid ceramide. Purified exosomes were enriched in ceramide, and the release of exosomes was reduced after the inhibition of neutral sphingomyelinases. These results establish a pathway in intraendosomal membrane transport and exosome formation.
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                Author and article information

                Journal
                Neurobiology of Disease
                Neurobiology of Disease
                Elsevier BV
                09699961
                June 2023
                June 2023
                : 182
                : 106141
                Article
                10.1016/j.nbd.2023.106141
                37121555
                82a4c5f1-f671-4bed-a39b-445a9d055326
                © 2023

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by/4.0/

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